A typical glassware manufacturing plant includes a forming machine, also known in the trade as an individual section or IS machine, and a "gob feeder" mechanism. A forming machine typically includes 6-10 identical individual sections for producing finished glassware such as bottles or jars. The gob feeder mechanism feeds a gob of molten glass to each of the sections of the forming machine in turn. As an article of glassware issues from each of the sections, it is carried by a conveyor through an inspection area where the glassware is inspected for flaws. The flaw inspection is normally accomplished by either the actual observation of a human being stationed at the inspection area or by a video camera inspection system.
Three areas of a glass container are generally inspected for flaws. The top and thread area is inspected for defects on the seal surface and for thread flaws. The sidewall of the container is inspected for defects in the glass container walls such as cracks, bubbles, bird-swings, etc. The bottom surface area of the container is inspected for a long list of flaws that include, among others, loose and fused glass, spikes, bird-swings, stones and bubbles, and mold dope.
Most glassware is manufactured to bear some indication of its origin by placement of certain mold markings on the outside base of the container. These markings may take the form of letters, numbers, or abstract designs. The presence of the various types of markings plus the fact that the same markings do not always appear in the same physical location has made automatic inspection of glass bottoms inherently difficult.
Moreover, most troublesome is the "baffle mark" formed in the bottom surface of a glass container. The baffle mark is a mold marking which is a by-product of the two-step glass manufacturing process and is generally circular in shape and may appear in different locations on the bottom of the container. It is generally an acceptable (by glass manufacturer and user) condition. In the automatic inspection of glassware by optical systems, the baffle mark can produce a high contrast signal which is often confused with the signal from a defect, thereby resulting in the rejection of acceptable glassware.
A defect in the glass represents an optical boundary layer which reflects or refracts an incident light beam producing a light contrast which can be detected optically. The great disadvantage of known optical test arrangements of this type consists in that they cannot distinguish between actual defects and other optically effective faults in the test element. For example, there are many types of faults, such as small included air bubbles, relatively small ribs or seams, etc., which do not have any deleterious effect on glassware, but which act similarly to a defect in optical test arrangements so that acceptable glassware is rejected. Because of the inability to distinguish between unacceptable defects and faults that can be tolerated, prior systems have been prone to accept defective glassware or, with more sensitive settings, to reject acceptable glassware.
Further, in detecting defects in glass articles, the articles have usually been illuminated with a diffused backlight, and viewed with a television camera or light sensitive sensor array. The light source often consists of a plurality of incandescent bulbs that produce generally a relatively large diffused source for backlighting the container at the inspection station or zone. A linear array television camera, focused on a portion of the container to be inspected, will provide an image of that portion onto the array of picture elements (commonly referred to as "pixels") in the camera. The pixels then are serially interrogated and the outputs of the pixels, which is a function of the intensity of the light received thereon, are compared. Defects in the container portion being inspected can be detected by analysis of the pixel outputs of the linear array.
In such systems, when a defect appears in the container as that portion is moved through the field of view area of the camera, the pixels upon which the portion is being focused will see areas of darkness caused by the reflection of the illuminated light out of the line of sight of the pickup. In this way, by comparing the output of adjacent pixels one can determine where the defect lies and the size of the defect. The pixels may be scanned at a sufficient rate so that essentially every area of the bottle is viewed. Most defects actually will span more than a single scan and will appear in several successive scans.
It has further been the practice to optically detect defects in glassware in various portions of a glass article by focusing a beam of light onto an area of the article at a particular angle and then positioning a pickup, such as a photocell, at approximately a 90.degree. angle with respect to the direction of the focused light. In such an arrangement, the light will be reflected from the defect onto the photocell, thus indicating the presence of a reflective defect. This has been the typical practice for examining the finish and heel portions of glass containers in the past. Defects which are being detected by such systems are those typically termed "checks", caused usually by thermal shocks during the formation of the container from the touching of the hot formed glass to a cold piece of handling equipment. Another defect which can be picked up by the use of specular, focused light are surface defects produced in glass containers which will cause the focused light to be refracted out of the direction in which it is being transmitted to the container, for example, a line-over-finish defect.
Another means by which glassware may be inspected is a machine vision system. Machine vision is the technology of acquiring or sensing an image (a visual impression) of a selected portion of the glassware through an electronic sensor and determining the existence of any marks or defects in the image and the acceptability of any such marks or defects by use of a computer. The technology is based around a television camera to acquire the image and dedicated vision computers to process and analyze the images from components/products with speed and repeatability. While human vision may outperform its automatic equivalent in its sheer ability to analyze very complex, every-day scenes; when it comes to repeated tasks, such as inspection of a product over and over again, a human observer understandably tires, loses concentration, and makes mistakes.
Machine vision can also be more cost-effective and sometimes the only viable solution if speed and/or hazardous conditions are present in the manufacturing process. The possible uses of machine vision technology include assembly/process verification, gauging, character verification and recognition, surface flaw detection, sorting systems, and robotic guidance. In many of these applications, machine vision systems can also provide important and accurate process control information since 100 percent of the product can generally be examined. This information can help identify the "problem area(s)" of the process so it can be corrected to reduce scrap and improve quality.
As noted above, automatic electro-optical inspection of glassware is well known; however, machine vision inspection methods of glass containers have developed only recently. A significant distinction between the two methods of inspection is the manner by which each system captures the image of the object being inspected and then analyzes that image to form an opinion on its status, i.e., acceptability.
Electro-optical scanning for glass bottom inspection has provided the glass manufacturer and the end user (prior to filling operations) with automatic inspection of their product for years. One such conventional system is shown in FIG. 1 wherein the system utilizes a diffused back light with an incandescent source. The empty glass container travels through the optical path by the dedicated material handling system (a star-wheel mechanism, for example). While the jar is in the optical path, it is scanned by a rotating prism which projects a revolving image of the bottom of the container through a lens onto a series of photosensors. Each sensor then scans a circular band area with all the sensors in combination providing complete coverage of the jar bottom. The signals from the sensors are fed into electronic discrimination circuits which analyze the incoming signal for changes/absolute values in the light level for defect detection.
The system is simple in principal and operation but requires precision part placement. This normally is achieved by some form of star-wheel mechanism that requires changeover parts to adapt the system for inspection of different container sizes/shapes. Poor repeatability in sensitivity setup, inability to examine non-round containers, and high false reject rates with the high sensitivity settings are among the shortcomings of such prior electro-optical scanning systems.
Machine vision inspection of glass containers offers some worthwhile advantages over the more established electro-optical scanning methods. These include sophisticated image processing/analysis, highly repeatable setup and performance, TV camera image available for easy diagnosis and setup, ability to inspect non-round containers, less precision in required part placement, and easier change over for other container shapes/sizes.
The basic components of a machine vision system include a material handling system, a lighting system, image acquiring means and image processing means. The material handling system manipulates and presents the part to the machine vision imaging system and generally includes the part sensing (photo-eye, proximity switch, etc.) and a defect removal mechanism. Machine vision systems can be either adapted to an existing material handling system, or a specific material handling system can be designed for the parts to be inspected.
The lighting system of a machine vision system illuminates the parts to be inspected. High contrast between the feature of interest (e.g., a defect) and its background (the non-defective area surrounding the defect) is desirable. The lighting system should also reduce the effects of unwanted feature information and provide the user with a stable, long-lasting and environmentally safe light source for inspection.
Two important aspects of a lighting system include the lighting technique and the light source. The lighting technique refers to the physical arrangement of the light source in relation to the part under inspection and the television camera. The lighting technique in its most fundamental concept is divided into front lighting and back lighting. Either can be accomplished with the use of structured or unstructured light.
Front lighting refers to the technique where the light source and the television camera are on the same side of the part being inspected. The angles and distances between the light source, part and camera are important and will determine the contrast of the image. Front lighting is generally used to view and extract surface features of objects.
Back lighting refers to lighting systems in which the light source and the television camera are on opposite sides of the object being inspected. This technique produces a high contrast silhouette image of an optically opaque object. With transparent objects such as glass containers, the contrast is produced by features changing light transmission, and/or light reflection, and/or light refraction.
The general list of illumination sources for machine vision include incandescent lamps, fluorescent lamps, xenon flash tubes, light emitting diodes, lasers and x-rays. For packaging or manufacturing applications, generally a strobe light is needed since the inspection is performed on moving objects. Two common strobe lights are the xenon flash tubes and light emitting diodes.
A light emitting diode (LED) is a solid state device which emits light when forward biased. The LEDs can be turned on and off quickly; therefore, they can act as a strobe light in a similar manner to the xenon flash. Generally, several LEDs form a strobe light with a single trigger and drive circuit to produce adequate light to illuminate an object. The LEDs are generally driven with current pulses much higher than the normal continuous operation currents to produce a short, but bright, pulse of light.
The optical components of a machine vision system normally include a lens that is attached to the image acquiring means defined by a television camera. Through this lens, an image of the object to be inspected is formed. The focal length of this lens and standoff distance (distance between the object and the lens) will determine the field of view. The field of view is preferably kept to a minimum to provide the system with the most accurate image interpretation and yet allow for normal part position variation. Two basic types of lenses include fixed focal length and variable focal length or zoom lens.
Other optical components include mirrors, beam splitters (partially silvered mirrors that can reflect and transmit light at the same time), color filters, polarizers, etc. These additional components are used to either enhance contrast and/or reduce the effect of unwanted information, or obtain the needed optical geometric arrangement in a limited space.
The most common image acquiring or sensing means used with machine vision applications is the solid state CCD- (charge coupled device) or MOS- (metal oxide semiconductor) type black and white television camera. The light sensor in these cameras is constructed of hundreds of thousands of individual solid state light sensitive elements (pixels) which are arranged in a matrix.
The high speed inspection of packaging lines require additional features that are generally not available on most cameras. One such feature has to do with the asynchronous timing relationship between the part's arrival at the inspection area in front of the camera and the camera's internal timing sequences. The typical part velocity is such that no delay between part arrival and picture acquisition can be tolerated; therefore, the camera's timing signals must be interrupted to allow it to acquire an image of the object immediately. This feature is sometimes referred to as "frame reset" capability and is only available on cameras designed for machine vision or similar scientific applications.
There are many different vision processors commercially available today for use with machine vision systems to process and analyze the image once acquired. Some are designed for specific tasks while some are meant as general purpose platforms. Most systems, however, will acquire and store a two-dimensional image from the television camera and then process and analyze the image by some form of computer. There are also many variations on the image processing and analysis algorithms. Often the machine vision hardware is designed for efficient implementation of those algorithms to achieve the high product throughput of packaging and pharmaceutical lines.
Three different basic arrangements of machine vision hardware are common and these are: dedicated hardware processors; parallel processors; and multiple processors.
Dedicated hardware processors are types of machine vision hardware in which the image processing/analysis algorithms are either partially or fully implemented in electronics hardware. This type of approach makes sophisticated high speed (greater than 2000 ppm) inspection possible. However, since the inspection algorithms are generally fixed in hardware, they are difficult to change for further enhancement and/or adoption to a new task.
The parallel processor technique relies on multiple processing networks that operate on the same image. This type of approach can provide high speed and sophisticated inspection techniques and maintain some flexibility in algorithm approach.
The multiple processor approach utilizes multiple complete-image acquire and process channels that share the incoming images from the television camera to speed up the system throughput. By increasing the number of processing channels, the higher throughput speeds are achieved. This type of multiprocessor software-based approach offers flexibility in algorithm selection and processing for high speed applications.
A major shortcoming in the application of conventional machine vision systems to the inspection of conventionally made glassware is their inability to deal with the baffle marks formed in the bottom surface of a glass container. Thus, there has developed a need for a means and method of inspecting the bottom surface of a glass container having a baffle mark formed therein to distinguish the acceptable baffle mark from unacceptable defects present in the bottom surface to effect the removal of unacceptable containers from the manufacturing system.